Issue |
MATEC Web Conf.
Volume 139, 2017
2017 3rd International Conference on Mechanical, Electronic and Information Technology Engineering (ICMITE 2017)
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Article Number | 00029 | |
Number of page(s) | 5 | |
DOI | https://doi.org/10.1051/matecconf/201713900029 | |
Published online | 05 December 2017 |
Research on the Intrusion Detection Method Based on Differentiated Cluster Center Offset Measure
1 School of Information Science and Engineering, Lanzhou University, Lanzhou, China
2 Lanzhou Municipal Public Security Bureau, Lanzhou, China
* Corresponding author: chenyu15@lzu.edu.cn
In this paper, a kind of local outlier mining method based on differentiated cluster center offset measure is proposed through which the outlier degree of sample can be calculated by use of the normal behavior model constructed by normal data sample and the preset anomaly threshold value, and whether the testing sample belong to intrusion behavior can thus be determined. Furthermore, KDD99 data set is also utilized to test the said method, and the experimental results show that the method proposed in this paper possesses higher detection rate and lower false alarm rate.
Key words: Intrusion detection; / Anomaly detection; / Outlier mining; / Cluster center offset
© The Authors, published by EDP Sciences, 2017
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (http://creativecommons.org/licenses/by/4.0/).
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